aboutsummaryrefslogtreecommitdiff
path: root/rand/examples
diff options
context:
space:
mode:
Diffstat (limited to 'rand/examples')
-rw-r--r--rand/examples/monte-carlo.rs39
-rw-r--r--rand/examples/monty-hall.rs10
2 files changed, 21 insertions, 28 deletions
diff --git a/rand/examples/monte-carlo.rs b/rand/examples/monte-carlo.rs
index 9162996..39c779f 100644
--- a/rand/examples/monte-carlo.rs
+++ b/rand/examples/monte-carlo.rs
@@ -11,7 +11,7 @@
//!
//! Imagine that we have a square with sides of length 2 and a unit circle
//! (radius = 1), both centered at the origin. The areas are:
-//!
+//!
//! ```text
//! area of circle = πr² = π * r * r = π
//! area of square = 2² = 4
@@ -24,28 +24,25 @@
//! the square at random, calculate the fraction that fall within the circle,
//! and multiply this fraction by 4.
-#![cfg(feature="std")]
-
-
-extern crate rand;
+#![cfg(feature = "std")]
use rand::distributions::{Distribution, Uniform};
fn main() {
- let range = Uniform::new(-1.0f64, 1.0);
- let mut rng = rand::thread_rng();
-
- let total = 1_000_000;
- let mut in_circle = 0;
-
- for _ in 0..total {
- let a = range.sample(&mut rng);
- let b = range.sample(&mut rng);
- if a*a + b*b <= 1.0 {
- in_circle += 1;
- }
- }
-
- // prints something close to 3.14159...
- println!("π is approximately {}", 4. * (in_circle as f64) / (total as f64));
+ let range = Uniform::new(-1.0f64, 1.0);
+ let mut rng = rand::thread_rng();
+
+ let total = 1_000_000;
+ let mut in_circle = 0;
+
+ for _ in 0..total {
+ let a = range.sample(&mut rng);
+ let b = range.sample(&mut rng);
+ if a*a + b*b <= 1.0 {
+ in_circle += 1;
+ }
+ }
+
+ // prints something close to 3.14159...
+ println!("π is approximately {}", 4. * (in_circle as f64) / (total as f64));
}
diff --git a/rand/examples/monty-hall.rs b/rand/examples/monty-hall.rs
index 0932c5e..9fe5839 100644
--- a/rand/examples/monty-hall.rs
+++ b/rand/examples/monty-hall.rs
@@ -26,13 +26,10 @@
//!
//! [Monty Hall Problem]: https://en.wikipedia.org/wiki/Monty_Hall_problem
-#![cfg(feature="std")]
+#![cfg(feature = "std")]
-
-extern crate rand;
-
-use rand::Rng;
use rand::distributions::{Distribution, Uniform};
+use rand::Rng;
struct SimulationResult {
win: bool,
@@ -40,8 +37,7 @@ struct SimulationResult {
}
// Run a single simulation of the Monty Hall problem.
-fn simulate<R: Rng>(random_door: &Uniform<u32>, rng: &mut R)
- -> SimulationResult {
+fn simulate<R: Rng>(random_door: &Uniform<u32>, rng: &mut R) -> SimulationResult {
let car = random_door.sample(rng);
// This is our initial choice